1. Risk Prediction in Clinical Practice Joann G. Elmore MD, MPH SCCA June 11, 2014

2. Overview 1.Risk prediction models need to work well for individual patients to be helpful in individual counseling. 2. Both clinicians and patients (and the media) must understand the numeric information resulting from risk prediction models in order to use them effectively.

3. All Patients Risk Prediction Models Ultra Low Risk Medium Risk High Risk

4. All Patients Risk Prediction Models Ultra Low Risk Medium Risk High Risk

5. All Patients Ultra Low Risk Medium Risk High Risk Risk Prediction Models

6. http://www.cancer.gov/bcris ktool/

7. Validation of Gail Model at the Population Level The Gail model works well at the population level, with calibration calculated at 0.94 (B Rockhill, et al JNCI 2001) 1.01 (WE Barlow et al JNCI 2006) 1.03 (JA Tice et al Ann Intern Med 2008)

8. Validation of Gail Model Population vs. Individual Risk Population of women 0% to 100% Individual woman Either 0% or 100%

9. Ideal Model Estimated Five-year Risk of Breast Cancer Excellent Discrimination (c-statistic=1.0) (All Women with Risk > "X" Value get Cancer) Women with Cancer Women with no Cancer Proportion of Sample Low Risk X High Risk

10. Gail Model Estimated Five-year Risk of Breast Cancer C-statistic 0.58

11. 80,755 50,000 100,000 Women with Cancer Women with no Cancer 1.67% cutoff Gail Model Example Estimated Five-year Risk of Breast Cancer Gail Risk Value

12. For every 47 women classified as high-risk only 1 will subsequently be diagnosed with breast cancer (Sensitivity 0.44; Specificity 0.66)      Performance of Gail Model using a 5-year cancer risk of 1.67%     

13. Clinical Experience “Doctor, what is my risk of getting breast cancer?” 41-year-old patient

14. What is a 41-year-old woman’s risk of breast cancer over the next 5 years? A 41-year-old white woman whose mother had breast cancer, who had one prior breast biopsy with atypical hyperplasia, who was age 40 at first live birth. What is her risk of a breast cancer diagnosis in the next 5 years? A. Less than 4% B. 10% C. 20% D. 50%

15. What is a 41-year-old woman’s risk of breast cancer over the next 5 years?

16. Radiologists’ Estimates of the 5-year risk of a breast cancer diagnosis. “A 41-year old white woman...” Calculated risk Egger, et al., Med Dec Making, 2005

17. Numeric Literacy Example Question High School Diploma or less Post- graduate degree How many heads in 1,000 coin flips? 62%86% Convert 1% to # of patients in 1,000 60%82% LM Schwartz and S Woloshin 2000; G Gigerenzer et al, 2008 Convert 1 in 1,000 to a percentage 23%27%

18. Gigerenzer G etal., Psychol Sci Public Interest 2007

19. Variation of Lumpectomy Rates by Hospital Referral Region (2003-04) Dartmouth Atlas

20. Effect of Nancy Reagan’s Mastectomy Nattinger et al. JAMA 1998

21. Screening for Cancer (www.areyoudense.org) Treatment Decisions (e.g., Adjuvant!) Referral to Hospice (e.g., estimating 6-mo cut-off)

22. The Doctor (2014) www.myopennotes.org

24. Conclusions 1.Risk prediction models work well in populations, but not (yet) for individual patients. 2. Implementation into clinical practice and communication about risks is challenging. 3. The impact and value of these models in clinical practice needs to be studied.

25. Thank you

26. The Doctor by Sir Luke Fildes (1887)